Update README.md

README.md

@@ -20,15 +20,17 @@ This dataset contains 100 images of various fruits and vegetables captured under
 
 The data consists of RGB images, sparse spectral samples and instance segmentation masks.
 
-From the 100 images, we extract >430,000 spectral samples, of which >85,000 belong to one of the 18 classes in the dataset. The rest of the spectra can be used for negative sampling when training classifiers.
+From the 100 images, we extract >430,000 spectral samples, of which >85,000 belong to one of the 19 classes in the dataset. The rest of the spectra can be used for negative sampling when training classifiers.
 
 ### Classes
 
-The dataset contains 18 classes:
+The dataset contains 19 classes:
  - lemon - 8275 total samples
  - melon - 9507 total samples
  - yellow pepper - 4752 total samples
  - cucumber - 227 total samples
+ - granny smith apple - 3984 total samples
+ - jazz apple - 272 total samples
  - plastic apple - 6693 total samples
  - pink lady apple - 17311 total samples
  - royal gala apple - 21319 total samples
@@ -39,7 +41,6 @@ The dataset contains 18 classes:
  - orange - 4641 total samples
  - easy peeler orange - 2720 total samples
  - orange pepper - 552 total samples
- - jazz apple - 272 total samples
  - pear - 194 total samples
  - green grape - 106 total samples
  - lime - 43 total samples